In my recent academic article ( https://link.springer.com/content/pdf/10.1007/s44427-025-00019-y.pdf ) I analyzed a divide in how open-source software projects evolve, which might explain the difference in productivity boosts developers experience when using AI tools. The data shows that productivity on large, mature open-source projects was not significantly affected by any tech hypes over the last two decades, the commits reaching the main branches followed steady growth trends. At the same time, smaller projects presented much more chaotic growth trends, but also tended to lose speed and stall out much faster. As the study contains data till early 2025, it looks like even the publicly available LLMs till then, were not able to greatly increase the number of changes merged into the main branches of these projects. Could it happen, that the difference in productivity gain developers experience, is simply a function of project scale and environmental/organizational constraints? What has been your experience depending on the size of the codebase you work on? submitted by /u/MelodicStep6956
Originally posted by u/MelodicStep6956 on r/ArtificialInteligence